Understanding the Implications of Online Learning for Educational Productivity

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2 Understanding the Implications of Online Learning for Educational Productivity U.S. Department of Education Office of Educational Technology Prepared by: Marianne Bakia Linda Shear Yukie Toyama Austin Lasseter Center for Technology in Learning SRI International January 2012

3 This report was prepared for the U.S. Department of Education under Contract number ED- 01-CO-0040 Task 0010 with SRI International. The views expressed herein do not necessarily represent the positions or policies of the Department of Education. No official endorsement by the U.S. Department of Education is intended or should be inferred. U.S. Department of Education Arne Duncan Secretary Office of Educational Technology Karen Cator Director January 2012 This report is in the public domain. Authorization to reproduce this report in whole or in part is granted. While permission to reprint this publication is not necessary, the suggested citation is: U.S. Department of Education, Office of Educational Technology, Understanding the Implications of Online Learning for Educational Productivity, Washington, D.C., This report is available on the Department s Web site at On request, this publication is available in alternate formats, such as Braille, large print, or computer diskette. For more information, please contact the Department s Alternate Format Center at (202) or (202) Technical Contact: Bernadette Adams Yates bernadette.adams.yates@ed.gov

4 Contents Exhibits... ii Acknowledgements... iii Executive Summary... v Introduction... 1 Overview of Online Learning for Secondary Education... 1 Purpose of this Report... 3 Introduction to the Measurement of Educational Productivity... 5 Estimating Program Costs... 8 Documenting Context and Implementation Measuring Program Outcomes Cost-Effectiveness Research Requirements The Productivity Potential of Online Learning Opportunities to Reduce Educational Costs Through Online Learning Implications The Need for Transformation Suggestions for Future Research Appendix A: Additional Resources... A-1 General Productivity in Education... A-2 Productivity and Educational Technology... A-3 Key Resources on Types and Prevalence of Online Learning... A-13 Quality Standards for Online Learning Programs... A-15 References... A-17 i

5 Exhibits Exhibit 1: Components of Educational Productivity Analyses... 7 Exhibit 2: Comparison of Per-Pupil Spending ii

6 Acknowledgements This issue brief was developed under the guidance of Karen Cator and Bernadette Adams Yates of the U.S. Department of Education, Office of Educational Technology. At SRI International, Marie Bienkowski, Barbara Means and Robert Murphy provided advice and insightful feedback on earlier drafts of the report. Ashley Lee and Allison Steele provided research assistance. The report was edited by Michael Smith. Kate Borelli produced graphics and layout. The authors made their best attempt to incorporate the thoughtful guidance provided by reviewers of earlier drafts of this report, including Cathy Cavanaugh (University of Florida), Fiona Hollands (Teachers College, Columbia University), Kemi Jona (Northwestern University), Glenn Kleiman (Friday Institute for Educational Innovation), Robin Lake (University of Washington) and Henry Levin (Teachers College, Columbia University). The authors are grateful for their constructive comments. iii

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8 Executive Summary Educational systems are under increasing pressure to reduce costs while maintaining or improving outcomes for students. To improve educational productivity, 1 many school districts and states are turning to online learning. In the United States, online learning alternatives are proliferating rapidly. Recent estimates suggest that 1.5 million elementary and secondary students participated in some form of online learning in 2010 (Wicks 2010). The term online learning can be used to refer to a wide range of programs that use the Internet to provide instructional materials and facilitate interactions between teachers and students and in some cases among students as well. Online learning can be fully online, with all instruction taking place through the Internet, or online elements can be combined with face-to-face interactions in what is known as blended learning (Horn and Staker 2010). The purpose of this report is to support educational administrators and policymakers in becoming informed consumers of information about online learning and its potential impact on educational productivity. The report provides foundational knowledge needed to examine and understand the potential contributions of online learning to educational productivity, including a conceptual framework for understanding the necessary components of rigorous productivity analyses, drawing in particular on cost-effectiveness analysis as an accessible method in education. Five requirements for rigorous cost-effectiveness studies are described: 1) Important design components of an intervention are specified; 2) Both costs and outcomes are measured; 1 As defined in this report, productivity is a ratio between costs and outcomes that can be improved in one of three ways: by reducing costs while maintaining outcomes, improving outcomes while maintaining costs or transforming processes in a way that both reduces costs and improves outcomes. Any improvements in productivity are likely to require initial investments, but successful efforts reduce costs over the long term, even after these initial investments are taken into account. v

9 3) At least two conditions are compared; 4) Costs and outcomes are related using a single ratio for each model under study; 5) Other factors not related to the conditions being studied are controlled or held constant. The report also includes a review of ways that online learning might offer productivity benefits compared with traditional place-based schooling. Unfortunately, a review of the available research that examined the impact of online learning on educational productivity for secondary school students was found to be lacking. No analyses were found that rigorously measured the productivity of an online learning system relative to place-based instruction in secondary schools. 2 This lack of evidence supports the call of the National Educational Technology Plan (U.S. Department of Education 2010a) for a national initiative to develop an ongoing research agenda dedicated to improving productivity in the education sector. The evidence summarized in this report draws on literature that addressed either costs or effectiveness. These studies typically were limited because they did not bring the two together in a productivity ratio and compare results with other alternatives. Given the limitations of the research regarding the costs and effects of online instruction for secondary students, the review that follows also draws on examples and research about the use of online learning for postsecondary instruction. While there are many differences between higher education and elementary and secondary education (e.g., age and maturity of students), postsecondary institutions have a broader and longer history with online learning than elementary and secondary schools. The intention is to use the literature from higher education to illustrate concepts that may apply to emerging practices in elementary and secondary education. Findings from the studies of higher education should be applied with caution to secondary education, as student populations, learning contexts and financial models are quite different across these levels of schooling. While rigorously researched models are lacking, the review of the available literature suggested nine applications of online learning that are seen as possible pathways to improved productivity: 2 Two research reports an audit for the Wisconsin State Legislature (Stuiber et al. 2010) and a study of the Florida Virtual School (Florida Tax Watch Center for Educational Performance and Accountability 2007) include data about costs and effects. These reports suggest that online learning environments may hold significant potential for increasing educational productivity. Both found that online learning environments produced better outcomes than face-to-face schools and at a lower per-pupil cost than the state average. However, these conclusions must be viewed cautiously because both reports lacked statistical controls that could have ruled out other explanations of the findings. vi

10 1) Broadening access in ways that dramatically reduce the cost of providing access to quality educational resources and experiences, particularly for students in remote locations or other situations where challenges such as low student enrollments make the traditional school model impractical; 2) Engaging students in active learning with instructional materials and access to a wealth of resources that can facilitate the adoption of research-based principles and best practices from the learning sciences, an application that might improve student outcomes without substantially increasing costs; 3) Individualizing and differentiating instruction based on student performance on diagnostic assessments and preferred pace of learning, thereby improving the efficiency with which students move through a learning progression; 4) Personalizing learning by building on student interests, which can result in increased student motivation, time on task and ultimately better learning outcomes; 5) Making better use of teacher and student time by automating routine tasks and enabling teacher time to focus on high-value activities; 6) Increasing the rate of student learning by increasing motivation and helping students grasp concepts and demonstrate competency more efficiently; 7) Reducing school-based facilities costs by leveraging home and community spaces in addition to traditional school buildings; 8) Reducing salary costs by transferring some educational activities to computers, by increasing teacher-student ratios or by otherwise redesigning processes that allow for more effective use of teacher time; and 9) Realizing opportunities for economies of scale through reuse of materials and their large-scale distribution. It is important to note that these pathways are not mutually exclusive, and interventions intended to increase productivity usually involve multiple strategies to impact both the benefit side (pathways 1 4) and cost side (pathways 5 9). Determining whether online learning is more or less cost-effective than other alternatives does not lend itself to a simple yes or no answer. Each of the nine pathways suggests a vii

11 plausible strategy for improving educational productivity, but there is insufficient evidence to draw any conclusions about their viability in secondary schools. Educational stakeholders at every level need information regarding effective instructional strategies and methods for improving educational productivity. Studies designed to inform educational decisions should follow rigorous methodologies that account for a full range of costs, describe key implementation characteristics and use valid estimates of student learning. Even less is known about the impact of online learning for students with disabilities. Regarding potential benefits, the promise of individualized and personalized instruction suggests an ability to tailor instruction to meet the needs of students with disabilities. For example, rich multimedia can be found on the Internet that would seem to offer ready inspiration for meeting the unique needs of the blind or the hearing impaired. In fact, standards for universal design are available both for the Web and for printed documents. In addition, tutorial models that rely on independent study are well suited to students with medical or other disabilities that prevent them from attending brick-and-mortar schools. However, while online learning offerings should be made accessible to students with disabilities, doing so is not necessarily cheap or easy. Any requirement to use a technology, including an online learning program, that is inaccessible to individuals with disabilities is considered discrimination and is prohibited by the Americans with Disabilities Act of 1990 and Section 504 of the Rehabilitation Act of 1973, unless those individuals are provided accommodations or modifications that permit them to receive all the educational benefits provided by the technology in an equally effective and equally integrated manner. The degree to which programs make such accommodations is not yet known. To address this need, the U.S. Department of Education recently funded the Center on Online Learning and Students With Disabilities, a five-year research effort to identify new methods for using technology to improve learning. Similarly, research regarding the degree to which current online learning environments meet the needs of English language learners and how technology might provide a cost-effective alternative to traditional strategies is just emerging. The realization of productivity improvements in education will most likely require a transformation of conventional processes to leverage new capabilities supported by information and communications technologies. Basic assumptions about the need for seat time and age-based cohorts may need to be reevaluated to sharpen focus on the needs and interests of all students as individuals. And as a rigorous evidence accumulates around effective practices that may require institutional change, systemic incentives may be needed to spur the adoption of efficient, effective paths to learning. viii

12 Policymakers and educators do not yet have the needed rigorous evidence to answer some seemingly basic questions about when, how and under what conditions online learning can be deployed cost-effectively. More research is required to guide the deployment of online learning to its greatest effect. Research approaches should explicitly consider educational productivity. Organizational research is also needed to understand the incentives and barriers to employing the most cost-effective approaches to quality education for all students. ix

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14 Introduction The need to do more with less is an imperative for decision makers in nearly every economic sector. Education is no exception. State and local education systems face the dual challenges of improving outcomes while confronting budgetary declines. Reducing costs without sacrificing quality, or doing better with what is available, requires improvements in productivity (see Definition of Productivity sidebar). Productivity improvements is one of the primary goals of the online learning systems that are rapidly proliferating in secondary education. This report is intended to summarize what we know to date about productivity as it relates to online learning and to offer guidance to policymakers who are faced with the decision of whether and how to implement this strategy. Definition of Productivity Productivity is defined as the relationship between program inputs (measured in terms of financial value or time) and outcomes and outputs (including both quantitative measures and measures of outcome quality). Productivity can be increased by reducing costs while maintaining outcomes relative to other alternatives, improving outcomes while maintaining costs or both reducing costs and improving outcomes. Overview of Online Learning for Secondary Education The available evidence suggests that schools are using information technologies with the intention of expanding access, improving instructional quality and reducing costs associated with traditional instruction. Many districts and states have turned to online learning (see Definition of Online Learning sidebar) to replace or supplement teaching in brick-andmortar schools. For example, journal accounts indicate that some schools and districts are ending traditional summer school programs, instead providing instruction via the Internet (Krafcik 2010; Olster 2010). Schools are also contracting with online providers to deliver courses that they do not feel they could otherwise afford. 1

15 As of late 2010, online learning opportunities were made available to students in 48 states and Washington, D.C. These opportunities were offered by a number of different providers, including state virtual schools, multidistrict fulltime online schools, single-district programs and programs run by consortia or postsecondary institutions (Watson et al. 2010). Companies in the private sector also provide online learning opportunities for secondary students. According to survey-based estimates by the International Association for K-12 Online Learning (inacol), 1.5 million students took one or more online courses in 2010 (Wicks 2010). In these courses, students received all or part of their instruction over the Internet and interacted online with teachers, peers and digital learning content. Some states such as Alabama, Florida and Michigan have made the online learning experience part of their graduation requirements (Watson et al. 2010). Online learning has become popular because of its perceived potential to provide more flexible access to content and instruction by 1) increasing the availability of learning experiences for those who cannot or choose not to attend traditional schools, Definition of Online Learning Online learning refers to instructional environments supported by the Internet. Online learning comprises a wide variety of programs that use the Internet within and beyond school walls to provide access to instructional materials as well as facilitate interaction among teachers and students. Online learning can be fully online or blended with face-to-face interactions. Each of these approaches is described below. Fully online learning is a form of distance education in which all instruction and assessment are carried out using online, Internet-based delivery (Picciano and Seaman 2009; U.S. Department of Education 2007). In this brief, both teacher-led instruction and resources designed to instruct without the presence of a teacher meet the definition of fully online learning if they include instructional environments accessed exclusively through the Internet. Blended learning (also called hybrid learning) allows students to receive significant portions of instruction through both face-to-face and online means. Researchers see blended learning in the middle of the spectrum between fully face-to-face and fully online instruction (Graham, Allen, and Ure 2005; U.S. Department of Education 2007; Watson et al. 2010). 2) assembling and disseminating instructional content more efficiently, and 3) increasing student-instructor ratios while achieving learning outcomes equal to those of traditional classroom instruction. Some proponents see technology as having potential beyond increasing efficiency in instructional delivery, for example, by providing a community of learners to support understanding of a complex body of knowledge (Riel and Polin 2004; Schwen and Hara 2004). Online technologies can expand and support such communities by promoting 2

16 participatory education models rather than simply changing education delivery modes (Barab, Squire, and Dueber 2000; Barab and Thomas 2001). Others argue that online learning can provide individualized and differentiated instruction (Archambault et al. 2010; Christensen and Horn 2008; Waldeck 2008; Watson and Gemin 2008) through multiple mechanisms that provide immediate formative feedback about a student s performance (Dennen 2005; Rice et al. 2008) or through modularized content that enables learning the same content at a different pace or to achieve different learning goals. The distinction between fully online and blended learning is important in part because it helps set the standard for comparing costs and outcomes (Watson et al. 2010; U.S. Department of Education 2010b). To be viewed as a success, online programs that provide access to courses or programs that would otherwise be unavailable need to be as effective as traditional alternatives. Blended approaches are typically perceived as quality improvements that enhance and improve traditional instruction but as such need to demonstrate gains in learning quality or rate of learning to justify the additional expenses. Although the terms fully online and blended are commonly used and conceptually useful, blended learning itself can take many forms, and models of blended instruction are still emerging. If either fully online or blended instruction can transform instructional processes, there is an opportunity to improve quality as well as reduce costs. 3 Purpose of this Report Because online learning is serving increasing numbers of secondary students, it is essential to understand whether, when and how particular implementations of online learning are equally or more productive than other forms of instruction. The purpose of this report is to support educational administrators and policymakers in becoming informed consumers of information about online learning and its potential impact on educational productivity. The report provides foundational knowledge needed to examine and understand the potential productivity contributions of online learning and reviews the research that describes how online learning might offer productivity benefits compared with traditional brick-and-mortar schooling. 3 The literature describes traditional designs as offering the online equivalent of simple didactic instruction (e.g., programs in which the system provides content to read and a quiz at the end), whereas transformational designs provide a fundamentally different student experience. See Watson et al. [2010] for a more detailed description of transformational practices in one state virtual school. 3

17 This report includes a framework for understanding general principles associated with systematic productivity analyses in education; a summary of claims regarding how online learning could affect educational productivity; a review of the literature that informs understanding of the costs and effects of online learning relative to traditional face-to-face instruction; a discussion of the implications of the findings; and brief summaries of specific resources for readers wanting to learn more about topics addressed (appendix). Ultimately, the hope is that this information can be used to help educators realize productivity improvements in the future. 4

18 Introduction to the Measurement of Educational Productivity A number of publications describe formal analytic procedures for estimating the productivity of countries (e.g., Organisation for Economic Co-operation and Development [OECD] 2008), industries (e.g., Colecchia and Schreyer 2001) and firms (e.g., Brinkerhoff and Dressler 1990). In education, productivity is typically understood as a ratio of the cost of inputs per output, with outputs often measured in terms of student academic attainment (Cohn and Geske 1990; Levin and McEwan 2001). The academic literature provides at least three frameworks for analyzing educational productivity. Levin and McEwan (2001) present a series of detailed frameworks for the rigorous analysis of costs and outcomes specific to educational interventions. Rumble (1997) and Kaestner (2007) apply similar frameworks specifically for distance learning and online learning. With rare exceptions, productivity analyses typically require that at least one other alternative to the option under study be examined because cost-effectiveness and similar ratios are relative. As suggested above, there are several methodologies used to measure productivity. These methods all measure costs and are often classified by the type of outcome measure used. This report focuses primarily on what is known as a cost-effectiveness approach because effectiveness data are in many cases available in education and because these outcome measures, such as test scores, retention rates and school attendance, are considered meaningful and consequential in educational contexts, especially in K Cost-benefit approaches, which calculate monetary value for outcomes of interest in order to create a dollars-to-dollars comparison, are often used to support decisions about government programs because they allow comparison of projects across industries (e.g., health and education). However, this type of study can be particularly challenging in education, both because of the difficulties associated with assigning monetary value to many educational outcomes (such as test scores) and because measurements of the types of outcomes that are more readily monetized (such as impact on wages and income over time) would rely on data not currently collected or readily available. Cost-effectiveness studies often have two goals: (1) to inform decisions about a particular program under way in a particular location and (2) to inform other stakeholders as they consider undertaking new programs of their own. To accomplish these goals, studies must 4 Educational attainment measures are consequential in the sense that they are used to determine grade progression, college attendance, etc. 5

19 both measure the productivity of the online learning intervention relative to other alternatives and describe key elements of the intervention that will be needed for replication of the program elsewhere. Cost-effectiveness ratios are helpful only in the context of comparable ratios based on realistic alternatives, which in turn suggests the need for consensus among analysts regarding the comparability of those alternatives. For example, a cost-effectiveness study might look at the cost of a range of alternatives for raising student achievement in math by an average of 10 points per student. When the results of the analysis are expressed this way, they can be used to compare similar costs and outcomes across design alternatives. Studies such as these can inform a host of decisions related both to currently operational and to planned online learning environments. For example, educational administrators could ask Would online learning help us serve more summer school students at less cost without sacrificing outcomes? Over the last 3 years, has our online learning system been more or less productive than our traditional brick-and-mortar alternatives in terms of the cost per completer, average grades or test scores? Is this ratio likely to change over the next three years? How do blended and strictly online versions of a given course compare in terms of the cost to improve students learning outcomes? Clearly, depending on the question to be answered, different sources of data will be needed. Although the costs and outcomes for any online learning system will vary according to its design and scope, both costs and outcomes in education generally fall within a common set of categories that can be used to guide cost and outcome measurement (Exhibit 1). 6

20 Exhibit 1: Components of Educational Productivity Analyses Note: The bullets provided in each category in this exhibit are representative rather than comprehensive. Exhibit reads: Several different kinds of costs account for final cost estimates developed in educational productivity studies. 7

21 Estimating Program Costs The ingredients approach to specifying costs adapted from Levin and McEwan (2001) suggests determining all the types of costs associated with developing and running a program and assigning a value to each (see appendix for additional resources that look at this approach more deeply). Although specific costs will vary by program, they can be summarized using the categories in Exhibit 1. Personnel costs include the time of teachers, teaching assistants, developers, administrators and any others involved in creating or running the online learning system. Facilities costs include the costs of buildings, classrooms, office space and furniture for administrative and instructional purposes as well as for housing computers. Equipment and infrastructure costs include the resources required to implement needed technology, support its operation and maintain the equipment and infrastructure in working order. Materials and supplies costs include purchased online curricula or textbooks, as well as other physical goods or processes (e.g., the costs associated with printing and copying). The other category varies by implementation model but usually includes general operational services and student supports required for the successful and legal operation of the program or school. If productivity analyses of online and other instructional practices are to become more routine, accounting systems at every level of education need to better identify costs in each of these categories. A few basic considerations for cost analyses are as follows: Rigorous cost analyses include the costs or value of all resources essential to an intervention as well as its most realistic alternative, and the same types of costs are included for each alternative so that apples are compared with apples. For example, the initial costs associated with program planning and curriculum development are often important considerations for new online systems. Similarly, investments in technology such as hardware and connectivity are often required before starting an online learning program. On the other hand, facilities costs can be sizable for more traditional instructional approaches. In estimating the costs of each alternative, costs of planning, curriculum development and 8

22 facilities should be treated similarly across alternatives. 5 Significant mismatches across cost estimates can lead to erroneous conclusions. All components of a program, regardless of the source of funding, should be included. For example, teachers time may be covered by their contracts and therefore not entail an additional cost incurred by the online learning program. However, if teachers spend time providing online instruction, the system incurs an opportunity cost for other possible uses of those hours that are lost. The same is true of shared resources such as computer labs, even if the computers were not purchased specifically for the online learning program. Available time, data and budgets for cost-effectiveness research will also shape the precision of cost estimates and the rigor of outcomes research. In most circumstances, it would be prohibitively expensive to arrive at a fully accurate cost, and it is often difficult to obtain accurate records of each component cost. Accordingly, most studies include some level of estimation. The balance of actual and estimated costs is a function of many factors, including the time and funding available for the productivity study, the accuracy of available records, the research team s access to cost data that may be proprietary and the goals of the study. Precision is more important for some purposes than for others. Specific line items in the framework may require a combination of actual and estimated costs; for example, it is relatively easy to identify hourly teacher salaries, but individual teachers may not have tracked the hours they spent in developing curriculum for an online learning program. Similarly, information about student motivation is often considered on an ad hoc basis if at all. Questions about systems currently being implemented should be supported by data on actual costs and outcomes; analyses of future or planned systems will necessarily rely on estimates based on historical spending and on costs/outcomes for similar systems. In estimating costs, the same parameters should be used across conditions so that estimates are comparable. In studies that compare an online learning system with a traditional model, state per-pupil education expenditures are a common proxy for the per-pupil costs of the traditional condition. However, that proxy should be used with care, because neighborhood schools typically include a wide 5 Cost analysts use mathematical procedures to develop annual costs for investments that may be purchased in one year but used across several years. For example, if a computer is purchased, the annual cost of the hardware would be based on the initial cost divided by the estimated life of the computer (often considered three years) and may include additional adjustments. Ongoing costs like computer maintenance should also be considered. A more detailed treatment of costing procedures is beyond the scope of this report, but related resources are provided in the appendix for the reader interested in learning more. 9